Curating operational historian data for distribution via a communication network

ABSTRACT

Targeted distributing of reports containing historical process control information to particular user devices via a communications network. A curating service permits assigning a score to each report based on an interest level value of the historical process control information to a user associated with each user device and/or an urgency value of the historical process control information. Routing reports to user devices based on the score raises visibility of the historical process control information without overburdening the communications network.

CROSS-REFERENCE TO RELATED APPLICATION

This application claims priority from U.S. Provisional PatentApplication Ser. No. 62/221,424, filed Sep. 21, 2015, entitled“Operational Historian Data Pattern Detection and CommunicationServices.” The entire contents of the above-identified application areexpressly incorporated herein by reference, including the contents andteachings of any references contained therein.

TECHNICAL FIELD

Aspects of the present disclosure generally relate of the fields ofnetworked computerized industrial control automation systems andnetworked computerized systems utilized to monitor, log, and displayrelevant manufacturing/production events and associated data, andsupervisory level control and manufacturing information systems. Moreparticularly, aspects of the present disclosure relate to systems andmethods for transforming stored data into actionable metrics fortransmitting to various devices.

BACKGROUND

Such systems generally execute above a regulatory control layer in aprocess control system to provide guidance to lower level controlelements such as, by way of example, programmable logic controllers ordistributed control systems (DCSs). Such systems are also employed toacquire and manage historical information relating to industrialprocesses and their associated outputs. “Historization” is a vital taskin the industry as it enables analysis of data representing historicalinformation to improve industrial processes.

Typical industrial processes are extremely complex and receivesubstantially greater volumes of information than any human couldpossibly digest in its raw form. By way of example, it is not unheard ofto have thousands of sensors and control elements (e.g., valveactuators) monitoring/controlling aspects of a multi-stage processwithin an industrial plant. These sensors are of varied type and reporton varied characteristics of the process. Their outputs are similarlyvaried in the meaning of their measurements, in the amount of data sentfor each measurement, and in the frequency of their measurements. Asregards the latter, for accuracy and to enable quick response, some ofthese sensors/control elements take one or more measurements everysecond. Multiplying a single sensor/control element by thousands ofsensors/control elements (a typical industrial control environment)results in an overwhelming volume of data flowing into the manufacturinginformation and process control system. Distributing the entire volumeof data all user devices overburdens communications networks andunnecessarily utilizes network resources by sending data irrelevant tousers associated with one or more user devices.

SUMMARY

Aspects of the disclosure permit targeted distributing of reportscontaining Information that is of interest to particular users via acommunications network. A curating architecture permits scoring eachreport based on interest level values and/or urgency level values.Routing reports to user devices based on the scores raises visibility ofhistorical process control information without overburdening thecommunications network.

A method embodying aspects of the disclosure includes a curating serviceretrieving reports from a report database. Each report includeshistorical data relating to process control tags associated with aprocess control system. The curating service comprisesprocessor-executable instructions executing on a processor. The curatingservice assigns a score to each retrieved report based on an interestlevel value and/or an urgency value. A scored report is routed from thecurating service, by transmission via a communications network, to auser device when its score is at least equal to a threshold value. Inresponse to the transmission, the report displays on the user device.

A system embodying aspects of the disclosure includes a processor, acomputer-readable storage device, a report database, and a curatingservice. The report database stores reports that each includeshistorical data relating to process control tags associated with aprocess control system. The curating service comprisesprocessor-executable instructions stored on the computer-readablestorage device. When executed by the processor, the instructionsretrieve reports from the report database, assign a score to eachretrieved report based on an interest level value and/or an urgencyvalue, and route a scored report to a user device. The scored report isrouted by transmitting it via a communications network to the userdevice when the score is equal to or greater than a threshold value. Inresponse to the transmission, the report displays on the user device.

Other objects and features will be in part apparent and in part pointedout hereinafter.

BRIEF DESCRIPTION OF THE DRAWINGS

FIG. 1 illustrates an operational historian data pattern detection andcommunication services system according to an embodiment.

FIG. 2 illustrates a reporting service of the operational historian datapattern detection and communication services system of FIG. 1.

FIG. 3 is an exemplary flow diagram illustrating an operation of thereporting service of FIG. 2.

FIG. 4 is an exemplary flow diagram illustrating an operation of acurating service of the operational historian data pattern detection andcommunication services system of FIG. 1.

FIG. 5 is an exemplary flow diagram illustrating an operation of analert service of the operational historian data pattern detection andcommunication services system of FIG. 1

FIG. 6 is an exemplary flow diagram illustrating an operation of asearch service of the operational historian data pattern detection andcommunication services system of FIG. 1

FIG. 7 illustrates an exemplary architecture of a computing deviceprogrammed to provide aspects of the operational historian data patterndetection and communication services system of FIG. 1.

FIG. 8 is an exemplary flow diagram illustrating an operation of thereporting service to provide unsupervised anomaly detection intime-series data according to another embodiment.

FIGS. 9-12 illustrate an exemplary pressure profile of a pipe in anindustrial process that carries water over a period of days according toan embodiment.

FIG. 13 illustrates an exemplary industrial process system within whichaspects of the disclosure may be incorporated.

FIG. 14 illustrates an exemplary display of a user-specific reportcollection and/or a general report collection displayed by a graphicaluser interface according to an embodiment.

Corresponding reference characters indicate corresponding partsthroughout the drawings.

DETAILED DESCRIPTION

Referring to FIG. 1, an operational historian data pattern detection andcommunication services system, generally indicated at 100, analyzes datastored in an operational historian and transforms that data into timelyreports that are communicated to appropriate devices at appropriatetimes and manners. In this manner, aspects of the system 100 filters(e.g., curates) the data in order to raise visibility of the data tousers (e.g., via user devices) without overwhelming them and/oroverburdening communications networks. The system 100 includes anoperational historian 102, a reporting service 104, a report database106, a curating service 108, a user-specific report collection 110, ageneral report collection 112, an alert service 114, and a searchservice 116. In an embodiment, system 100 provides a historian news feedof generated reports (i.e., stories) for users based on data provided byan operational historian and/or other providers.

In an embodiment, the operational historian 102 is adapted to store(e.g., “historize”) various types of data related to an industrialprocess. Exemplary data includes, but is not limited to, time-seriesdata, metadata, event data, configuration data, raw time-series binarydata, tag metadata, diagnostic log data, and the like. The operationalhistorian 102 is also adapted to record trends and historicalinformation about the industrial process for future reference. Anexemplary operational historian 102 stores data about various aspects ofan industrial process in quantities that humans cannot interpret oranalyze. For example, an operational historian may receive two millionor more data values (e.g., tags relating to process control components,process variables, etc.) every second. In an embodiment, historian 102comprises processor-executable instructions embodied on a storage memorydevice (e.g., as part of a server computing device) to provide theoperational historian 102 via a software environment. An exemplaryoperational historian 102 includes Wonderware® Historian and Wonderware®Online provided by Schneider Electric.

The reporting service 104 illustrated by FIG. 1 is adapted to retrievedata from operational historian 102, detect patterns in the retrieveddata, generate reports that include information about the detectedpatterns, and store the generated reports in the report repository, suchas a database 106. In an embodiment, reporting service 104 comprisesprocessor-executable instructions embodied on a storage memory device toprovide reporting service 104 via a software environment. For example,reporting service 104 may be provided as processor-executableinstructions that comprise a procedure, a function, a routine, a method,and/or a subprogram utilized independently or in conjunction withadditional aspects of system 100 by computing device 103 according to anexemplary embodiment of the disclosure. Further details of reportingservice 104 are provided herein.

In an embodiment, reporting service 104 is adapted to retrieve data fromoperational historian 102 by transmitting a query to operationalhistorian 102, which operational historian 102 receives and uses toselect stored data that matches the query. The operational historian 102then transmits the selected data to reporting service 104. The reportingservice 104 may retrieve data continuously or at regular intervals. Inthe embodiment illustrated by FIG. 2, reporting service 104 retrievesand/or receives data from additional sources, including externalthird-party reporting applications 206 (e.g., via an ApplicationProgramming Interface (API) of reporting service 104), built-inreporting services (e.g., Wonderware® Online built-in reporters) 208,application specific reporting services based on a client applicationconfiguration 210, and a Human Machine Interface (HMI) 212. It will beunderstood by one having skill in the art that additional reportingentities may be utilized to extend the capability of reporting service104. For example, a framework for adding additional reporting services104 gives aspects of the disclosure extensibility and “verticals”readiness.

Referring again to the embodiment of FIG. 1, reporting service 104 isadapted to analyze the data using algorithms and to detect certainpatterns (e.g., “pattern of interest”) and/or non-conformities in thedata. Exemplary algorithms include statistical algorithms, machinelearning algorithms, rules-based algorithms, and the like. Upondetecting certain patterns, reporting service 104 generates reportsabout these detected patterns. In an exemplary embodiment, a reportincludes text, graphics (e.g., graphs, images, etc.), and metadata. Thereports may include the information about the detected patterns in aformat that is amenable to the curating service 108 and/or a format thatis human-understandable when displayed via a display device and/or aHuman Machine Interface device. In this manner, reporting service 104transforms the data from a format that is unintelligible to curatingservice 108 and humans into a format that is intelligible to curatingservice 108 and humans when displayed via a device.

After generating the reports, reporting service 104 transmits thereports to the report database 106 for storage. The reporting service104 is configurable to transmit the reports to report database 106 viaan HTML interface, a REST interface, an ODATA interface, and similarinterfaces. In an embodiment, system 100 includes a plurality ofreporting services 104 that each retrieve data from operationalhistorian 102, detect patterns in the data, generate reports, and storethe reports in report database 106. In an embodiment that utilizes aplurality of reporting services, each reporting service may operateindependently or the collective operating services may operate inparallel on portions of a larger reporting task.

The report database 106 is adapted to store reports as an organizedcollection of data. In this manner, report database 106 stores thereports in a central location for access by various systems and devices.

Still referring to FIG. 1, curating service 108 is adapted tointelligently review reports stored in database 106, rank and/orclassify reviewed reports, and route (e.g., distribute) ranked reportsto collections, devices, other services, and the like. In an embodiment,curating service 108 moderates reports and raises their visibility tousers at a certain frequency and in a certain manner such that userswill not be overwhelmed with data, but instead will be provided withuseful information in the reports at times and manners that are mostappropriate for each specific user or groups of users. For example, foreach user, curating service 108 determines whether a particular reportshould appear on a primary/front page of a feed for that user, on asecondary page for that user, or just be archived in a searchable formatfor that user. By distributing relevant reports to certain user devices,curating service 108 reduces the burden on communications networks. Thecurating service 108 is configurable to take additional actions based onthe relevance of a particular report for a particular user, such as beepor alert a user device 118 of the user, as further described herein. Inanother embodiment, curating service 108 functions as a filter todetermine which of the multitude of reports in report database 106 aretransmitted to certain users and at which times those reports aretransmitted.

In an embodiment, curating service 108 comprises processor-executableinstructions embodied on a storage memory device to provide curatingservice 108 via a software environment. For example, curating service108 is embodied by processor-executable instructions that comprise aprocedure, a function, a routine, a method, and/or a subprogram utilizedindependently or in conjunction with additional aspects of system 100 bycomputing device 103 according to an exemplary embodiment of thedisclosure. Further details of curating service 108 are provided herein.

According to an embodiment of the disclosure, curating service 108 isadapted to utilize passive evaluation factors to intelligently reviewreports stored in database 106. As reports are received by database 106from reporting service 104, curating service 108 is adapted to give eachreport a general score and a per-user score based on various factors.Exemplary factors based on report content include, but are not limitedto, tags on the same chart, tags on the same window, tags on the sameanalysis, SmartGlance reports, tags from the same data source, tags withsimilar names, tags with similar summary statistics, correlated tags,and the like. Exemplary factors based on actions taken by users include,but are not limited to, selecting (e.g., clicking, tapping, etc. via aHMI) on a report, selecting a related tag, search history, actions ofsimilar users (e.g., operators of a particular subsystem, all operators,all managers, etc.), and the like. Actions taken by users may beprovided as feedback from user devices 118 to curating service 108, inan exemplary embodiment. The curating service 108 is also adapted toutilize factors based on deliberate user actions such as voting,answering polls on reports (e.g., “thumbs up”, “not a problem”, etc.),and the like. Furthermore, curating service 108 is adapted to utilize aspecific assignment of certain tags, process control devices, and thelike to a certain user in determining the general and per-user scores.

The curating service 108 illustrated in FIG. 1 is adapted to rank, foreach user or user group, reviewed reports based on report content anddata regarding user interest patterns. In an exemplary embodiment,curating service 108 ranks reports with respect to an operator of aparticular subsystem of an industrial process. When an intelligentreview of a report by curating service 108 reveals that the reportconcerns a component in the operator's subsystem, curating service 108is adapted to rank that report higher with respect to the operator thana report about a component in a different subsystem for which theoperator is not responsible. In another exemplary embodiment, curatingservice 108 is adapted to use data regarding component informationregularly viewed by the operator (e.g., via a user profile) and when anintelligent review of a report by curating service 108 reveals that thereport concerns a component that the operator regularly views curatingservice 108 is adapted to rank that report higher with respect to theoperator than a report about items that the operator does not regularlyview. In an embodiment, the ranking performed by curating service 108 isa numerical ranking or score. However, it will be understood by oneskilled in the art that any ranking or scoring mechanism may be utilizedthat indicates a higher relevance or importance of one report over adifferent report. In an embodiment, report ranking is made available toreporting service 104 which reporting service 104 uses to tailor reportgeneration to generate more highly ranked reports. In an embodiment,curating service 108 directs reports to user devices 118 based oncontext including, but not limited to, area(s) of interest, a user's ownevents, and events of other operators in a team.

The curating service 108 is also adapted to utilize the ranking ofreports to classify the reports and determine which actions to take withrespect to a particular report. For example, curating service 108classifies and routes reports based on a general interest level (e.g.,score), a user-specific interest level (e.g., score), and/or urgency. Inan exemplary embodiment, curating service 108 determines based on theranking of a report to not forward that report to any device or user butinstead continue to store the report in database 106 where it isavailable for accessing via the search service 116. In anotherembodiment, curating service 108 determines based on the ranking of areport to transmit the report to the user-specific report collection110. In another embodiment, curating service 108 determines based on theranking of a report to transmit the report to the general reportcollection 112. In yet another embodiment, curating service 108determines based on the ranking of a report to transmit the report inreal-time in the form of an alert to one or more user devices 118 via analert service 114. Additional actions curating service 108 may takebased on a classification of a report include displaying the report as anews story on a news feed, displaying the report as an activity onrelated trends, displaying the report only when searched via searchservice 116, and displaying reports on related process graphics (e.g.,displaying a line plot of a particular property of an industrial processwith its anomalies annotated).

As described above, curating service 108 classifies and routes reportsbased on urgency and/or other time-based factors according toembodiments of the present disclosure. For example, curating service 108determines that a report includes content that is time-sensitive and/orhighly consequential to an industrial process and transmit the report touser devices 118 via alert service 114 in addition to and/or rather thangeneral report collection 112. In another exemplary embodiment, curatingservice 108 analyzes the volume of reports generated by reportingservice 104 over a given time period (e.g., work shift, day, etc.) anddistributes reports accordingly. For example, when the volume of reportsgenerated by reporting service 104 is low during a particular day (e.g.,a “slow” news day), curating service 108 distributes fewer reports withlower rankings. In a contrasting example, when the volume of reportsgenerated by reporting service 104 is high during a particular day(e.g., a “fast” news day), curating service 108 distributes more andhigher ranked reports. Such an urgency-based operation of curatingservice 108 may also be used to distribute a consistent volume ofreports over a given time period (e.g., 100 reports per day, etc.) suchthat curating service 108 alters the ranking threshold in order toachieve the requisite number of reports. The urgency-based operation ofcurating service 108 may also be used alter the ranking threshold suchthat only highly ranked (e.g., 95 out of 100, etc.) reports arepublished during a certain time period (e.g., days that a manager isscheduled to be on vacation, etc.).

Still referring to FIG. 1, the user-specific report collection 110 isadapted to receive reports from curating service 108 and organize thereports into lists (e.g., feeds) that are kept current and madeavailable to users and/or groups of users via user devices 118. Forexample, user-specific report collection 110 may be a database,according to an aspect of the disclosure. In an embodiment,user-specific report collection 110 provides feeds that indicate newreports that have not yet been accessed by user devices 118 and/orreports that have not been displayed by user devices 118. The generalreport collection 112 is adapted to receive reports from curatingservice 108 and present them in a manner such that they may be browsedthrough via user devices 118. For example, general report collection 112may be a database, according to an aspect of the disclosure. Inexemplary embodiment, general report collection 112 organizes reports insuch a way to support navigation of the reports via user devices 118. Inanother exemplary embodiment, general report collection 112 organizesreports such that reports having higher general relevance to anindustrial process than other reports are stored in a manner such thatthose reports are displayed in more prominent positions when accessedand displayed via user devices 118.

Referring again to FIG. 1, alert service 114 is adapted to receivereports from curating service 108 and deliver received reports to userdevices 118 in real-time. For example, alert service 114 may deliverreports to user devices 118 in the form of emails, text messages, mobiledevice notifications (e.g., user interface notification), pagernotification, and the like. In an embodiment, alert service 114comprises processor-executable instructions embodied on a storage memorydevice to provide alert service 114 via a software environment. Forexample, alert service 114 may be provided as processor-executableinstructions that comprise a procedure, a function, a routine, a method,and/or a subprogram utilized independently or in conjunction withadditional aspects of system 100 by computing device 103 according to anexemplary embodiment of the disclosure. Further details of alert service114 are provided herein. In an embodiment, alerts from alert service 114are more important than reports.

The search service 116 of FIG. 1 is adapted to allow reports stored indatabase 106 to be searched via user devices 118. In an exemplaryembodiment, search service 116 is adapted to search database 106 forreports containing certain content. In another embodiment, searchservice 116 is adapted to search database 106 for reports by relation tohistorian entities involved in the reports. In an embodiment, searchservice 116 comprises processor-executable instructions embodied on astorage memory device to provide search service 116 via a softwareenvironment. For example, search service 116 may be provided asprocessor-executable instructions that comprise a procedure, a function,a routine, a method, and/or a subprogram utilized independently or inconjunction with additional aspects of system 100 by computing device103 according to an exemplary embodiment of the disclosure. Furtherdetails of search service 116 are provided herein.

The user devices 118 of FIG. 1 are adapted to receive from and transmitdata to user-specific report collection 110, general report collection112, alert service 114, and/or search service 116. In an embodiment,user devices 118 are also adapted to provide feedback on usagecharacteristics of the user devices 118 to curating service 108.Exemplary user devices 118 include, but are not limited to, personalcomputers, laptops, tablet computers, mobile communication devices,smartphones, and the like.

FIG. 3 illustrates an exemplary operation 300 of an embodiment ofreporting service 104. The reporting service 104 retrieves data fromoperational historian 102 at step 302. For example, reporting service104 may generate a request, including a query, for data and transmit therequest to operational historian 102. Upon receiving the request,operational historian 102 determines which stored data matches the queryand transmits that data to reporting service 104, which receives thatdata to complete the retrieval step 302. In another embodiment,operational historian 102 transmits all newly stored data to reportingservice 104 without a specific request or query from reporting service104. In an embodiment, the data stored by operational historian 102 andretrieved (e.g., received) by reporting service 104 relates to processcontrol tags associated with a process control system of an industrialprocess. At step 304, reporting service 104 analyzes the retrieved data.The analysis performed by reporting service 104 includes, for example,performing statistical algorithms and/or machine learning algorithms todetect patterns and/or non-conformities with patterns in the dataaccording to aspects of the disclosure. In an embodiment, reportingservice 104 determines and generates a prediction model representativeof expected values of the process control tags during step 304. Forexample, reporting service 104 may detect tag values that do not conformto a prediction model in order to identify information of interest tousers of aspects of system 100.

Referring again to the embodiment illustrated by FIG. 3, reportingservice 104 generates reports based on the analysis of the data at step306. In an embodiment, reporting service 104 generates reports aboutdetected patterns and/or non-conformities with patterns in the data. Inanother embodiment, reporting service 104 generates reports includingidentified information of interest to users of aspects of system 100.For example, the reports may include text, graphics, metadata,multimedia items, and the like that facilitate conveying characteristicsof detected patterns and/or non-conformities (e.g., anomalies,deviations, etc.) in the data to users via user devices 118 and/orfacilitate organizing or indexing the reports for access by devicesincluding user devices 118. The reporting service 104 transmits (e.g.,publishes) generated reports to report database 106 at step 308. Thereport database 106 stores the reports for access by various devices orservices, including curating service 108 and search service 116. In anembodiment, a processor executing the operations of FIG. 4 constitutes aspecial purpose computer for receiving historical data for analysis,receiving current data for analysis, analyzing the historical data todetermine a pattern in the values of the process control tags over theprevious intervals of time, detecting that the value of the current datais anomalous relative to the pattern to identify information of interestto one or more users, and publishing at least one report indicative ofthe detected non-conforming tag value into a report database.

FIG. 4 illustrates an exemplary operation 400 of an embodiment ofcurating service 108. The curating service 108 reviews reports stored indatabase 106 at step 402. For example, curating service 108 retrievesreports from database 106 and/or accesses reports stored in database106. At step 404, curating service 108 analyzes reports stored indatabase 106 and scores and/or ranks the reports according to passivesystem evaluation factors, passive user action evaluation factors,and/or active (e.g., deliberate) user action evaluation factors asfurther described herein. In an embodiment, curating service 108 makesreport scores/rankings available to reporting service 104 in a feedbackloop at step 406. For example, curating service 108 transmitsscores/rankings to reporting service 104 or reporting service 104 sendsa request to curating service 108 for scores/rankings. At step 408,curating service 108 classifies and/or routes reports according to ageneral interest level, a user-specific interest level, and/or anurgency level as further described herein. In an embodiment, a processorexecuting the operations of FIG. 4 constitutes a special purposecomputer for retrieving reports from the report database, assigning ascore to each retrieved report based on at least one of an interestlevel value and an urgency value, and routing a scored report to a userdevice when the score thereof is equal to or greater than a thresholdvalue.

FIG. 5 illustrates an exemplary operation 500 of an embodiment of alertservice 114. The alert service 114 receives reports from curatingservice 108 at step 502. For example, based on a score or ranking of areport, curating service 108 is configured to classify the report asneeding to be communicated to one or more user devices 118 (e.g., a useror group of users) via an alert and thus routes the report to alertservice 114. After receiving the alert, alert service 114 uses dataabout the intended user devices 118 to determine an appropriate alertmedium for the intended user devices 118 at step 504. For example, oneuser device 118 may be associated with a preference for a text messagewhile another user device 118 may be associated with a preference for anemail or phone notification. After determining the appropriate alertmedium, alert service 114 transmits the alert via the appropriate mediumto the intended user devices 118 at step 506.

FIG. 6 illustrates an exemplary operation 600 of an embodiment of searchservice 116. The search service 116 receives a search query from one ormore user devices 118 at step 602. At step 604, search service 116 usesthe search query to search for data stored in database 106 that matchesthe query. Upon determining data that matches the query, search service116 returns (e.g., transmits) the search results to the requesting userdevice 118 at step 606.

FIG. 7 illustrates an exemplary architecture of computing device 103programmed to provide aspects of the operational historian data patterndetection and communication services system 100 via a softwareenvironment. In this embodiment, computing device 103 includes aprocessor 702, a memory 704, and an input/output (I/O) interface 706that interfaces with an I/O component 708. The memory 704 includes anoperational historian interface 102′, reporting service 104, a reportdatabase 106′, curating service 108, user-specific report collection110, general report collection 112, alert service 114, and searchservice 116 each embodied in processor-executable instructions forexecuting by processor 702.

The processor 702, memory 704, and I/O interface 706 are communicativelyconnected and/or electrically connected to each other. The I/O interface706 is communicatively and/or electrically connected to the I/Ocomponent 708. The processor 702 is adapted to executeprocessor-executable instructions stored in the memory 704 forimplementing the operational historian interface 102′, reporting service104, report database interface 106′, curating service 108, user-specificreport collection 110, general report collection 112, alert service 114,and/or search service 116. The I/O interface 706 of FIG. 7 provides aphysical data connection between computing device 103 and I/O component708. In an embodiment, I/O interface 706 is a network interface card(NIC) or modem and I/O component 708 is a telecommunications network.

The operational historian interface 102′ of FIG. 7 is adapted to providea connection between computing device 103 and operational historian 102.In an exemplary embodiment, operational historian interface 102′retrieves and/or receives data from operational historian 102 via I/Ointerface 706, as further described herein. The report databaseinterface 106′ of FIG. 7 is adapted to provide a connection betweencomputing device 103 and a computer-readable storage medium storingreport databases 106. In an exemplary embodiment, report databaseinterface 106′ facilitates publishing of reports from reporting service104 to report database 106 via I/O interface 706, as further describedherein. In another embodiment, report database interface 106′facilitates access to report database 106 by curating service 108 andsearch service 116 via I/O interface 706, as further described herein.

FIG. 8 illustrates an exemplary operation of an embodiment of reportingservice 104 in which reporting service 104 is adapted to provideunsupervised anomaly detection in time-series data based on statisticaldeviations (e.g., anomalies) at certain intervals. For example, insteadof solely relying on alarm limits to detect anomalies in data stored inoperational historian 102, an embodiment of reporting service 104utilizes statistical methods to determine when a significant change hasoccurred in the characteristics of a signal indicative of a property ofan industrial process, as represented by data stored in operationalhistorian 102. Upon determining such a significant change, reportingservice 104 generates a report including information about the changeand publishes the report to report database 106 for review by users orother systems (e.g., curating service 108) to determine if the changerepresents a problem and/or interesting condition with respect to theindustrial process. In an embodiment, reporting service 104 checks foranomalies against different common intervals (e.g., time periods) forthe particular type of data rather than exclusively utilizing the mostrecent data from operational historian 102.

An exemplary situation involves an industrial process that includes apipe for conveying a pressurized fluid. A leak in the pipe may cause asmall drop in pressure, but if the pressure is still in an acceptablerange a conventional system based on alarm limits may fail to detect theleak. In contrast, an embodiment of reporting service 104 adapted toconduct a statistical analysis in accordance with FIG. 8 detects thatthe pressure within the pipe is outside of a normal range withoutneeding specific limits to be preconfigured. Upon retrieving data valuesfrom operational historian 102, reporting service 104 calculates atime-weighted mean value over a first interval at step 804-A, atime-weighted minimum value over the first interval at step 806-A, atime-weighted maximum value over the first interval at step 808-A, and atime-weighted standard deviation value over the first interval at step810-A. The reporting service then calculates a time-weighted mean valueover a second interval at step 804-B, a time-weighted minimum value overthe second interval at step 806-B, a time-weighted maximum value overthe second interval at step 808-B, and a time-weighted standarddeviation value over the second interval at step 810-B. In oneembodiment, reporting service 104 only calculates the values over twotime intervals. In another embodiment, reporting service 104 calculatesthe values over additional time intervals. Exemplary intervals include aprevious hour, a previous day, a previous week, a previous two weeks,and a previous month (e.g., the same day in the previous month). Otherexemplary intervals include a previous shift, a previous batch run, andthe like.

Still referring to FIG. 8, reporting service 104 determines, at step812, whether the calculated values (e.g., mean values, minimum values,maximum values, standard deviation values) differ by more than apredetermined amount over more than one interval, which indicates ananomaly. For example, reporting service 104 may determine whether thecalculated values over the multiple time periods differ by more than twostandard deviations. When reporting service 104 determines that thecalculated values differ by more than the predetermined amount, and thusindicates an anomaly, reporting service 104 generates a report includinginformation about the anomaly and publishes (e.g., transmits and stores)the report to report database 106 at step 814.

FIGS. 9-12 illustrate an exemplary pressure profile of a pipe in anindustrial process that carries water over a period of days. Utilizingthe pressure profile only during the time period generally indicated at902 as a baseline, reporting service 104 determines that an anomalyoccurs during the time period generally indicated at 904 because thepressure profile during period 904 differs from the pressure profileduring period 902 by more than a certain predetermined amount. However,as illustrated by FIG. 10, upon comparing the pressure profile duringperiod 904 to the pressure profile during period 906 (e.g., a differentbaseline), reporting service 104 determines that an anomaly has notoccurred during period 904 because it does not differ from the pressureprofile during period 906 by more than the predetermined amount. Asillustrated by FIG. 11, when reporting service 104 compares the pressureprofile during period 904 to pressure profiles across multiple intervals(e.g., both period 902 and period 906), reporting service 104 determinesthat the pressure profile during period 904 does not present an anomalybecause the pressure profile is not different over more than oneinterval and thus does not generate or publish a report.

Referring now to FIG. 12, reporting service 104 compares the pressureprofile of period 1202 to the pressure profiles at periods 1204 and1206. The reporting service 104 determines that the pressure profileduring period 1202 differs from both the pressure profile during period1204 and the pressure profile during period 1206 by more than a certainamount. Thus, reporting service 104 generates a report including theanomaly detected at period 1202 and publishes the report to reportdatabase 106. In an embodiment, reporting service 104 combinesstatistical detection with similar periods at natural period boundariesto improve the operation of anomaly detectors.

FIG. 13 illustrates an exemplary industrial process system 1300 withinwhich aspects of the disclosure may be incorporated. The system 1300includes computing device 103, operational historian device 101, reportdatabase 106, user devices 118, a communication network 1302, and anexemplary fluid processing system 1310. The operational historian device101 further includes operational historian 102. The fluid processingsystem 1310 of the exemplary embodiment of FIG. 13 further includes apump 1303, valves 1304, a sensor 1306, and process controller 1308. Insystem 1300, computing device 103, operational historian device 101,report database 106, user devices 118, and various components of thefluid processing system 1310 (e.g., pump 1303, valves 1304, sensor 1306,process controller 1308) are communicatively connected via thecommunication network 1302.

The communication network 1302 is capable of facilitating the exchangeof data among historian device 101, computing device 103, reportdatabase 106, user devices 118, and components of fluid processingsystem 1310. The communication network 1302 in the embodiment of FIG. 13is a local area network (LAN) that is connectable to othertelecommunications networks, including other LANs or portions of theInternet or an intranet. The communication network 1302 may be anytelecommunications network that facilitates the exchange of data, suchas those that operate according to the IEEE 802.3 (e.g., Ethernet)and/or the IEEE 802.11 (e.g., Wi-Fi) protocols, for example. In anotherembodiment, communication network 1302 is any medium that allows data tobe physically transferred through serial or parallel communicationchannels (e.g., copper, wire, optical fiber, computer bus, wirelesscommunication channel, etc.). In an embodiment, communication network1302 comprises at least in part a process control network.

The historian device 101 is adapted to provide operational historian102, which is adapted to store (e.g., “historize”) various types of datarelated to fluid processing system 1310, as further described herein.The computing device 103 is adapted to provide reporting service 104,report database 106 (or an interface to a computer-readable storagemedium storing report database 106), curating service 108, user-specificreport collection 110, general report collection 112, alert service 114,and search service 116, as further described herein. The report database106 is adapted to store reports generated by reporting service 104 as anorganized collection of data, as further described herein. The userdevices 118 are adapted to receive from and transmit data touser-specific report collection 110, general report collection 112,alert service 114, and/or search service 116, as further describedherein.

Still referring to FIG. 13, fluid processing system 1310 is adapted forchanging or refining raw materials to create end products. It will beapparent to one skilled in the art that aspects of the presentdisclosure are capable of optimizing processes and processing systemsother than fluid processing system 1310 and that system 1310 ispresented for illustration purposes only. Additional exemplary processesinclude, but are not limited to, those in the chemical, oil and gas,food and beverage, pharmaceutical, water treatment, and powerindustries. In an embodiment, process controller 1308 provides aninterface or gateway between components of fluid processing system 1310(e.g., pump 1303, valves 1304, sensor 1306) and other components ofsystem 1300 (e.g., historian device 101, computing device 103, reportdatabase 106, user devices 118). In another embodiment, components offluid processing system 1310 communicate directly with historian device101, computing device 103, report database 106, and user devices 118 viacommunication network 1302. In yet another embodiment, processcontroller 1308 transmits data to and receives data from pump 1303,valves 1304, and sensor 1306 for controlling and/or monitoring variousaspects of fluid processing system 1310.

FIG. 14 illustrates an exemplary display of user-specific reportcollection 110 and/or general report collection 112 displayed by agraphical user interface of user devices 118. The exemplary displaynotifies user devices 118 of significant events related to an industrialprocess. In an embodiment, the user interface provides a statusindicator when there are new reports available. Selecting the statusindicator (e.g., clicking, tapping, etc.) via user devices 118 causesuser devices 118 to display the selected report. As indicated at 1402,the display of user-specific report collection 110 and/or general reportcollection 112 includes a graphical indication (e.g., plotted datapoints) of anomalous data values. In an embodiment, the graphicalrepresentations of the anomalous data values are a different color fromthe graphical representations of the non-anomalous data values. Forexample, the graphical representations of the anomalous data values maybe red and the graphical representations of the non-anomalous datavalues may be green. In accordance with an aspect of the disclosure,graphically differentiating anomalous data values from non-anomalousdata values enables users of user devices 118 to readily identifyabnormal operating ranges of an industrial process (e.g., fluidprocessing system 1310).

In an exemplary embodiment of aspects of the disclosure, two reportingservices 104 are utilized. Both reporting services 104 use managedhistorian data to publish reports. Key Performance Indicator (KPI)monitoring reports on performance based on predefined KPIs and anomalydetection that analyzes data from operational historian 102 for anythingout of the normal and reports it. Reporting service 104 and curatingservice 108 generate and distribute reports on a daily basis reportinghow a process control environment of an industrial process is doingcompared to the KPI goals. In an embodiment, a user device 118 searchesfor “higher than usual” via search service 116 and displays many storieson a particular date saying “yesterday xxx was higher than usual.” Itturns out that the yesterday in point was the particular date and thusthe anomaly detector detected the anomaly. In an embodiment, aspects ofthe disclosure may be utilized in an Internet of Things (IoT)environment.

In an embodiment, aspects of the disclosure are utilized with userdevices 118 embodied as mobile devices with mobile apps. For example,aspects of the disclosure may be installed via app stores and aspectsmay be optimized for touchscreen embodiments. In other embodiments,aspects of the disclosure may be browser-based (e.g., served applicationthat showcases historian capabilities). In an embodiment, aspects of thedisclosure may be used as a productivity tool to allow debugging andanalysis for custom applications. In an embodiment, aspects of thedisclosure take advantage of capabilities including leveraging summarytags, leveraging model view and derivation view, and leveraging flexibleevents, data dictionary, and IHistory. Aspects of the disclosure utilizea technology stack including an HTML5 app (e.g., Angular.js and D3),modular components, and a managed historian. Aspects of the disclosureare component-based (e.g., value and time axis pieces can be sharedbetween all chart types). Exemplary modular components include charts,trends, grids, and the like.

Aspects of the disclosure include a method of detecting operationalchanges in an industrial process. The method comprises: receiving, by areporting service, historical data for analysis, the historical databeing stored in an operational historian associated with a processcontrol system, the historical data relating to a plurality of values ofa process control tag, each value corresponding to a previous intervalof time, and the reporting service comprising processor-executableinstructions executing on a processor; receiving, by the reportingservice, current data for analysis, the current data being stored in theoperational historian, and the current data relating to a value of theprocess control tag at a current interval of time; analyzing, by thereporting service, the historical data to determine a pattern in thevalues of the process control tags over the previous intervals of time;detecting, by the reporting service, that the value of the current datais anomalous relative to the pattern to identify information of interestto one or more users; and publishing, by the reporting service, at leastone report indicative of the detected non-conforming tag value into areport database.

In an embodiment, the historical data comprises at least one of timeseries data, metadata, and event data.

In an embodiment, the previous intervals of time are at least one of oneday, one week, two weeks, and one month.

In an embodiment, analyzing the historical data comprises performing astatistical analysis of the historical data for each previous intervalof time to determine the pattern from the historical data.

In an embodiment, the statistical analysis comprises at least one of atime-weighted mean value analysis, a time-weighted minimum valueanalysis, a time-weighted maximum value analysis, and a time-weightedstandard deviation analysis.

In an embodiment, detecting that the value of the current data isanomalous comprises determining the statistically analyzed historicaldata differs by more than a predetermined amount over more than one ofthe intervals of time.

In an embodiment, analyzing the historical data comprises executing amachine learning analysis to identify a correlation among two or morevalues of the process control tag over the previous intervals of time.

In an embodiment, executing the machine learning analysis comprises:training a prediction model representative of expected values of theprocess control tag over the previous intervals of time; testing theprediction model against a test dataset; and monitoring the historicaldata for the anomalous tag value.

In an embodiment, the previous intervals of time are at least one of oneday, one week, two weeks, and one month.

In an embodiment, said receiving historical data, said receiving currentdata, said analyzing, said detecting, and said publishing are eachperformed in real-time during the current interval of time.

Aspects of the disclosure also include a system comprising: a processor;a computer-readable storage device; and a reporting service, wherein thereporting service comprises processor-executable instructions stored onthe computer-readable storage device, wherein said instructions includeinstructions for, when executed by the processor: receiving historicaldata for analysis from an operational historian, the historical datarelating to a plurality of values of a process control tag associatedwith a process control system, each value corresponding to a previousinterval of time, receiving current data for analysis, the current datarelating to a value of the process control tag at a current interval oftime, analyzing the historical data to determine a pattern in theprocess control tag values over the previous intervals of time;detecting that the value of the current data is anomalous relative tothe pattern to identify information of interest to one or more users,and publishing at least one report indicative of the detected anomaloustag value relating to the current data.

In an embodiment, the historical data comprises at least one of timeseries data, metadata, and event data.

In an embodiment, the previous intervals of time are at least one of oneday, one week, two weeks, and one month.

In an embodiment, analyzing the historical data comprises performing astatistical analysis of the historical data for each previous intervalof time to determine the pattern from the historical data.

In an embodiment, the statistical analysis comprises at least one of atime-weighted mean value analysis, a time-weighted minimum valueanalysis, a time-weighted maximum value analysis, and a time-weightedstandard deviation analysis.

In an embodiment, detecting that the value of the current data isanomalous comprises determining the statistically analyzed historicaldata differs by more than a predetermined amount over more than one ofthe intervals of time.

In an embodiment, analyzing the historical data comprises executing amachine learning analysis to identify a correlation among two or morevalues of the process control tag over the previous intervals of time.

In an embodiment, executing the machine learning analysis comprises:training a prediction model representative of expected values of theprocess control tag over the previous intervals of time; testing theprediction model against a test dataset; and monitoring the historicaldata for the anomalous tag value.

In an embodiment, the previous intervals of time are at least one of oneday, one week, two weeks, and one month.

In an embodiment, said receiving historical data, said receiving currentdata, said analyzing, said detecting, and said publishing are eachperformed in real-time during the current interval of time.

Embodiments of the present disclosure may comprise a special purposecomputer including a variety of computer hardware, as described ingreater detail below.

Embodiments within the scope of the present disclosure also includecomputer-readable media for carrying or having computer-executableinstructions or data structures stored thereon. Such computer-readablemedia can be any available media that can be accessed by a specialpurpose computer. By way of example, and not limitation, suchcomputer-readable media can comprise RAM, ROM, EEPROM, CD-ROM or otheroptical disk storage, magnetic disk storage, or other magnetic storagedevices, or any other medium that can be used to carry or store desiredprogram code means in the form of computer-executable instructions ordata structures and that can be accessed by a general purpose or specialpurpose computer. When information is transferred or provided over anetwork or another communications connection (either hardwired,wireless, or a combination of hardwired or wireless) to a computer, thecomputer properly views the connection as a computer-readable medium.Thus, any such connection is properly termed a computer-readable medium.Combinations of the above should also be included within the scope ofcomputer-readable media. Computer-executable instructions comprise, forexample, instructions and data which cause a general purpose computer,special purpose computer, or special purpose processing device toperform a certain function or group of functions.

The following discussion is intended to provide a brief, generaldescription of a suitable computing environment in which aspects of thedisclosure may be implemented. Although not required, aspects of thedisclosure will be described in the general context ofcomputer-executable instructions, such as program modules, beingexecuted by computers in network environments. Generally, programmodules include routines, programs, objects, components, datastructures, etc. that perform particular tasks or implement particularabstract data types. Computer-executable instructions, associated datastructures, and program modules represent examples of the program codemeans for executing steps of the methods disclosed herein. Theparticular sequence of such executable instructions or associated datastructures represent examples of corresponding acts for implementing thefunctions described in such steps.

Those skilled in the art will appreciate that aspects of the disclosuremay be practiced in network computing environments with many types ofcomputer system configurations, including personal computers, hand-helddevices, multi-processor systems, microprocessor-based or programmableconsumer electronics, network PCs, minicomputers, mainframe computers,and the like. Aspects of the disclosure may also be practiced indistributed computing environments where tasks are performed by localand remote processing devices that are linked (either by hardwiredlinks, wireless links, or by a combination of hardwired or wirelesslinks) through a communications network. In a distributed computingenvironment, program modules may be located in both local and remotememory storage devices.

An exemplary system for implementing aspects of the disclosure includesa special purpose computing device in the form of a conventionalcomputer, including a processing unit, a system memory, and a system busthat couples various system components including the system memory tothe processing unit. The system bus may be any of several types of busstructures including a memory bus or memory controller, a peripheralbus, and a local bus using any of a variety of bus architectures. Thesystem memory includes read only memory (ROM) and random access memory(RAM). A basic input/output system (BIOS), containing the basic routinesthat help transfer information between elements within the computer,such as during start-up, may be stored in ROM. Further, the computer mayinclude any device (e.g., computer, laptop, tablet, PDA, cell phone,mobile phone, a smart television, and the like) that is capable ofreceiving or transmitting an IP address wirelessly to or from theinternet.

The computer may also include a magnetic hard disk drive for readingfrom and writing to a magnetic hard disk, a magnetic disk drive forreading from or writing to a removable magnetic disk, and an opticaldisk drive for reading from or writing to removable optical disk such asa CD-ROM or other optical media. The magnetic hard disk drive, magneticdisk drive, and optical disk drive are connected to the system bus by ahard disk drive interface, a magnetic disk drive-interface, and anoptical drive interface, respectively. The drives and their associatedcomputer-readable media provide nonvolatile storage ofcomputer-executable instructions, data structures, program modules, andother data for the computer. Although the exemplary environmentdescribed herein employs a magnetic hard disk, a removable magneticdisk, and a removable optical disk, other types of computer readablemedia for storing data can be used, including magnetic cassettes, flashmemory cards, digital video disks, Bernoulli cartridges, RAMs, ROMs,solid state drives (SSDs), and the like.

The computer typically includes a variety of computer readable media.Computer readable media can be any available media that can be accessedby the computer and includes both volatile and nonvolatile media,removable and non-removable media. By way of example, and notlimitation, computer readable media may comprise computer storage mediaand communication media. Computer storage media include both volatileand nonvolatile, removable and non-removable media implemented in anymethod or technology for storage of information such as computerreadable instructions, data structures, program modules or other data.Computer storage media are non-transitory and include, but are notlimited to, RAM, ROM, EEPROM, flash memory or other memory technology,CD-ROM, digital versatile disks (DVD) or other optical disk storage,SSDs, magnetic cassettes, magnetic tape, magnetic disk storage or othermagnetic storage devices, or any other medium which can be used to storethe desired non-transitory information, which can accessed by thecomputer. Alternatively, communication media typically embody computerreadable instructions, data structures, program modules or other data ina modulated data signal such as a carrier wave or other transportmechanism and includes any information delivery media.

Program code means comprising one or more program modules may be storedon the hard disk, magnetic disk, optical disk, ROM, and/or RAM,including an operating system, one or more application programs, otherprogram modules, and program data. A user may enter commands andinformation into the computer through a keyboard, pointing device, orother input device, such as a microphone, joy stick, game pad, satellitedish, scanner, or the like. These and other input devices are oftenconnected to the processing unit through a serial port interface coupledto the system bus. Alternatively, the input devices may be connected byother interfaces, such as a parallel port, a game port, or a universalserial bus (USB). A monitor or another display device is also connectedto the system bus via an interface, such as video adapter 48. Inaddition to the monitor, personal computers typically include otherperipheral output devices (not shown), such as speakers and printers.

One or more aspects of the disclosure may be embodied incomputer-executable instructions (i.e., software), routines, orfunctions stored in system memory or non-volatile memory as applicationprograms, program modules, and/or program data. The software mayalternatively be stored remotely, such as on a remote computer withremote application programs. Generally, program modules includeroutines, programs, objects, components, data structures, etc. thatperform particular tasks or implement particular abstract data typeswhen executed by a processor in a computer or other device. The computerexecutable instructions may be stored on one or more tangible,non-transitory computer readable media (e.g., hard disk, optical disk,removable storage media, solid state memory, RAM, etc.) and executed byone or more processors or other devices. As will be appreciated by oneof skill in the art, the functionality of the program modules may becombined or distributed as desired in various embodiments. In addition,the functionality may be embodied in whole or in part in firmware orhardware equivalents such as integrated circuits, application specificintegrated circuits, field programmable gate arrays (FPGA), and thelike.

The computer may operate in a networked environment using logicalconnections to one or more remote computers. The remote computers mayeach be another personal computer, a tablet, a PDA, a server, a router,a network PC, a peer device, or other common network node, and typicallyinclude many or all of the elements described above relative to thecomputer. The logical connections include a local area network (LAN) anda wide area network (WAN) that are presented here by way of example andnot limitation. Such networking environments are commonplace inoffice-wide or enterprise-wide computer networks, intranets and theInternet.

When used in a LAN networking environment, the computer is connected tothe local network through a network interface or adapter. When used in aWAN networking environment, the computer may include a modem, a wirelesslink, or other means for establishing communications over the wide areanetwork, such as the Internet. The modem, which may be internal orexternal, is connected to the system bus via the serial port interface.In a networked environment, program modules depicted relative to thecomputer, or portions thereof, may be stored in the remote memorystorage device. It will be appreciated that the network connectionsshown are exemplary and other means of establishing communications overwide area network may be used.

Preferably, computer-executable instructions are stored in a memory,such as the hard disk drive, and executed by the computer.Advantageously, the computer processor has the capability to perform alloperations (e.g., execute computer-executable instructions) inreal-time.

The order of execution or performance of the operations in embodimentsof the disclosure illustrated and described herein is not essential,unless otherwise specified. That is, the operations may be performed inany order, unless otherwise specified, and embodiments of the disclosuremay include additional or fewer operations than those disclosed herein.For example, it is contemplated that executing or performing aparticular operation before, contemporaneously with, or after anotheroperation is within the scope of aspects of the disclosure.

Embodiments of the disclosure may be implemented withcomputer-executable instructions. The computer-executable instructionsmay be organized into one or more computer-executable components ormodules. Aspects of the disclosure may be implemented with any numberand organization of such components or modules. For example, aspects ofthe disclosure are not limited to the specific computer-executableinstructions or the specific components or modules illustrated in thefigures and described herein. Other embodiments of the disclosure mayinclude different computer-executable instructions or components havingmore or less functionality than illustrated and described herein.

When introducing elements of aspects of the disclosure or theembodiments thereof, the articles “a”, “an”, “the” and “said” areintended to mean that there are one or more of the elements. The terms“comprising”, “including”, and “having” are intended to be inclusive andmean that there may be additional elements other than the listedelements.

Having described aspects of the disclosure in detail, it will beapparent that modifications and variations are possible withoutdeparting from the scope of aspects of the disclosure as defined in theappended claims. As various changes could be made in the aboveconstructions, products, and methods without departing from the scope ofaspects of the disclosure, it is intended that all matter contained inthe above description and shown in the accompanying drawings shall beinterpreted as illustrative and not in a limiting sense.

1-20. (canceled)
 21. A method of distributing reports over acommunications network to remote user devices, comprisingprocessor-executable instructions executing on a processor for:retrieving reports from a report database, wherein the reports eachinclude historical data relating to a plurality of process control tagsassociated with a process control system, wherein the process controltags have values representative of at least one of a component of theprocess control system and a process variable and at least some of thevalues correspond to an interval of time; detecting one or moreanomalies in the values based on statistical deviations at a pluralityof time intervals, wherein at least one of the reports identifiesinformation of interest indicative of at least one of the values at acurrent interval of time being anomalous relative to at least one of thevalues at a plurality of previous intervals of time; assigning a scoreto each retrieved report based on at least one of an interest levelvalue and an urgency value; and routing a scored report to a user devicefor display on a user device when the score thereof is at least equal toa threshold value.
 22. The method of claim 21, wherein the interestlevel value is specific to a user associated with the user device, saidspecificity based on responsibility for a process control tag assignedto the user.
 23. The method of claim 21, wherein the interest levelvalue is associated with a general interest level.
 24. The method ofclaim 21, wherein the interest level value is based on at least one oftags on the same chart, tags on the same window, tags on the sameanalysis, mobile report tags, tags from the same data source, tags withsimilar names, tags with similar summary statistics, and correlatedtags.
 25. The method of claim 21, wherein the urgency value is based ona quantity of the reports stored in the report database over a period oftime.
 26. The method of claim 21, wherein the urgency value is based onan importance of the report to the process control system.
 27. Themethod of claim 21, further comprising: generating an alert associatedwith a scored report when the score thereof is at least equal to thethreshold value; and transmitting the alert to the user device, whereinthe alert displays on the user device in response to said transmission.28. The method of claim 21, further comprising receiving feedback fromthe user device.
 29. The method of claim 28, wherein the feedbackincludes at least one of selecting a report displayed on the userdevice, selecting a process control tag related to a process control tagassociated with the report displayed on the user device, search history,polling, and actions by users similar to a user of the user device. 30.The method of claim 21, wherein said retrieving, assigning, and routingare each performed in real-time with an operation of a processcontrolled by the process control system.
 31. A system, comprising: aprocessor; a computer-readable storage device comprisingprocessor-executable instructions stored thereon, wherein saidinstructions include instructions for, when executed by the processor; areport database storing a plurality of reports, wherein the reports eachinclude historical data relating to a plurality of process control tagsassociated with a process control system, wherein the process controltags have values representative of at least one of a component of theprocess control system and a process variable and at least some of thevalues correspond to an interval of time; detecting one or moreanomalies in the values based on statistical deviations at a pluralityof time intervals, wherein at least one of the reports identifiesinformation of interest indicative of at least one of the values at acurrent interval of time being anomalous relative to at least one of thevalues at a plurality of previous intervals of time; and retrievingreports from the report database, assigning a score to each retrievedreport based on at least one of an interest level value and an urgencyvalue, and routing a scored report to a user device for display on theuser device when the score thereof is equal to or greater than athreshold value.
 32. The system of claim 31, wherein the interest levelvalue is specific to a user associated with the user device, saidspecificity based on responsibility for a process control tag assignedto the user.
 33. The system of claim 31, wherein the interest levelvalue is associated with a general interest level.
 34. The system ofclaim 31, wherein the interest level value is based on at least one oftags on the same chart, tags on the same window, tags on the sameanalysis, mobile report tags, tags from the same data source, tags withsimilar names, tags with similar summary statistics, and correlatedtags.
 35. The system of claim 31, wherein the urgency value is based ona quantity of the reports stored in the report database over a period oftime.
 36. The system of claim 31, wherein the urgency value is based onan importance of the report to the process control system.
 37. Thesystem of claim 31, wherein said instructions include instructions for,when executed by the processor: generating an alert associated with ascored report when the score thereof is greater than or equal to thethreshold value; and transmitting the alert to the user device, whereinthe alert displays on the user device in response to said transmission.38. The system of claim 31, wherein said instructions includeinstructions for, when executed by the processor, receiving feedbackfrom the user device.
 39. The system of claim 38, wherein the feedbackincludes at least one of selecting a report displayed on the userdevice, selecting a process control tag related to a process control tagassociated with the report displayed on the user device, search history,polling, and actions by users similar to a user of the user device. 40.The system of claim 31, wherein said retrieving, assigning, and routingare each performed by the processor in real-time with an operation of aprocess controlled at least in part by the process control system.